原创

精通Spring Boot教程(07):整合Redis实现缓存

1. 引言

项目中用到缓存是很常见的事情, 缓存能够提升系统访问的速度,减轻对数据库的压力等好处。今天我们来讲讲怎么在spring boot 中整合redis 实现对数据库查询结果的缓存。

2.实战

首先第一步要做的就是在pom.xml文件添加spring-boot-starter-data-redis。
要整合缓存,必不可少的就是我们要继承一个父类CachingConfigurerSupport。我们先看看这个类的源码

public class CachingConfigurerSupport implements CachingConfigurer {
    // Spring's central cache manage SPI ,
    @Override
    @Nullable
    public CacheManager cacheManager() {
        return null;
    }
    //key的生成策略
    @Override
    @Nullable
    public KeyGenerator keyGenerator() {
        return null;
    }
    //Determine the Cache instance(s) to use for an intercepted method invocation.
    @Override
    @Nullable
    public CacheResolver cacheResolver() {
        return null;
    }
    //缓存错误处理
    @Override
    @Nullable
    public CacheErrorHandler errorHandler() {
        return null;
    }

}

3.配置RedisConfig

RedisConfig类

@Configuration
@EnableCaching
public class RedisConfig extends CachingConfigurerSupport {

    @Bean
    RedisMessageListenerContainer container(RedisConnectionFactory connectionFactory, MessageListenerAdapter listenerAdapter) {
        RedisMessageListenerContainer container = new RedisMessageListenerContainer();
        container.setConnectionFactory(connectionFactory);
        container.addMessageListener(listenerAdapter, new PatternTopic("chat"));
        return container;
    }

    @Bean
    MessageListenerAdapter listenerAdapter(Receiver receiver) {
        return new MessageListenerAdapter(receiver, "receiveMessage");
    }

    @Bean
    Receiver receiver(CountDownLatch latch) {
        return new Receiver(latch);
    }

    @Bean
    CountDownLatch latch() {
        return new CountDownLatch(1);
    }


    public class Receiver {
        private CountDownLatch latch;

        @Autowired
        public Receiver(CountDownLatch latch) {
            this.latch = latch;
        }

        public void receiveMessage(String message) {
            latch.countDown();
        }
    }


    @Bean
    public KeyGenerator myKeyGenerator() {
        return new KeyGenerator() {
            @Override
            public Object generate(Object o, Method method, Object... objects) {
                StringBuilder sb = new StringBuilder();
                sb.append(o.getClass().getName());
                sb.append(method.getName());
                for (Object obj : objects) {
                    sb.append(JSON.toJSONString(obj));
                }
                return sb.toString();
            }
        };
    }

    /**
     * @param redisConnectionFactory
     * @return
     * @// TODO: 2018/4/27 redis fastjson序列化
     */
    @Bean
    @ConditionalOnMissingBean(name = "redisTemplate")
    public RedisTemplate<Object, Object> redisTemplate(RedisConnectionFactory redisConnectionFactory) {
        RedisTemplate<Object, Object> template = new RedisTemplate<>();
        //使用fastjson序列化
        FastJsonRedisSerializer fastJsonRedisSerializer = new FastJsonRedisSerializer<>(Object.class);
        // 全局开启AutoType,不建议使用
        // ParserConfig.getGlobalInstance().setAutoTypeSupport(true);
        // 建议使用这种方式,小范围指定白名单
        ParserConfig.getGlobalInstance().addAccept("com.developlee.models.");
        // value值的序列化采用fastJsonRedisSerializer
        template.setValueSerializer(fastJsonRedisSerializer);
        template.setHashValueSerializer(fastJsonRedisSerializer);
        // key的序列化采用StringRedisSerializer
        template.setKeySerializer(new StringRedisSerializer());
        template.setHashKeySerializer(new StringRedisSerializer());
        template.setConnectionFactory(redisConnectionFactory);
        return template;
    }

    @Bean
    @ConditionalOnMissingBean(StringRedisTemplate.class)
    public StringRedisTemplate stringRedisTemplate(RedisConnectionFactory redisConnectionFactory) {
        StringRedisTemplate template = new StringRedisTemplate();
        template.setConnectionFactory(redisConnectionFactory);
        return template;
    }

    /**
     * @return
     * @// TODO: 2018/4/27 设置redis 缓存时间 5 分钟
     */
    @Bean
    public RedisCacheConfiguration redisCacheConfiguration() {
        FastJsonRedisSerializer<Object> fastJsonRedisSerializer = new FastJsonRedisSerializer<>(Object.class);
        RedisCacheConfiguration configuration = RedisCacheConfiguration.defaultCacheConfig();
        configuration = configuration.serializeValuesWith(RedisSerializationContext.SerializationPair.fromSerializer(fastJsonRedisSerializer)).entryTtl(Duration.ofMinutes(5));
        return configuration;
    }
}

这段代码中,重点关注对象是RedisTemplate 和StringRedisTemplate还有RedisMessageListenerContainer,RedisTemplate和StringRedisTemplate设置了一些序列化的参数和指定序列化的范围(主要为了防止黑客利用Redis的序列化漏洞),@ConditionalOnMissingBean注解的意思就是如果容器中没有这个类型Bean就选择当前Bean。RedisMessageListenerContainer是为Redis消息侦听器提供异步行为的容器,主要处理低层次的监听、转换和消息发送的细节。

4. 配置application.yml

再来看看application.yml我们的配置 , so easy~~

spring:
   redis:
     database: 0  # Redis数据库索引(默认为0)
     host: 192.168.0.100 # Redis服务器地址 (默认为127.0.0.1)
     port: 6379    # Redis服务器连接端口 (默认为6379)
     password: 123456   # Redis服务器连接密码(默认为空)
     timeout: 2000  # 连接超时时间(毫秒)
  cache:
    type: redis

接下来我们就可以使用Redis缓存了,在Service层我们用注解@Cacheable来缓存查询的结果。

    @Cacheable(value= "orderDetailCache", keyGenerator = "myKeyGenerator", unless = "#result eq null")
    public OrderDetailEntity findOrderDetail(OrderDetailEntity orderDetailEntity) {
        return orderDetailDao.findEntity(orderDetailEntity);
    }

到这里我们就已经整合了Redis缓存了,是不是很简单的呢?自己多动手尝试哦!

最后,以上示例代码可在我的github.com中找到。

正文到此结束